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FORMS: Forest Multiple Source height, wood volume, and biomass maps in France at 10 to 30 m resolution based on Sentinel-1, Sentinel-2, and GEDI data with a deep learning approach.

Name: FORMS: Forest Multiple Source height, wood volume, and biomass maps in France at 10 to 30 m resolution based on Sentinel-1, Sentinel-2, and GEDI data with a deep learning approach.
Published: 2023-05-20
License: cc-by-4.0
Keywords: Canopy height, Biomass, Wood Volume, France, GEDI, Sentinel-2, Sentinel-1, Deep-learning, Forest, Carbon

Canopy height Biomass Wood Volume France GEDI

The products can be vizualized at https://martinschwartz0.users.earthengine.app/view/forms-height-biomass-volume-viewer - FORMS-H: Canopy height map of France at 10 m resolution. The units a

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CreatorSchwartz M.

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Published2023-05-20

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DOI10.5281/zenodo.7840108

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Downloads1,175

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Licensecc-by-4.0

File Size30.9 GB

Data TypeDataset

Published2023

Licensecc-by-4.0

Total Views2,050

Total Downloads1,175

The products can be vizualized at https://martinschwartz0.users.earthengine.app/view/forms-height-biomass-volume-viewer

– FORMS-H: Canopy height map of France at 10 m resolution. The units are in centimeter (10^-2 m).

– FORMS-B: Above-ground biomass density map of France at 30 m resolution. The units are in Mg ha-1

– FORMS-V: Wood volume density map of France at 30 m resolution. The units are in m3 ha-1

Please refer to the paper https://doi.org/10.5194/essd-15-4927-2023 for further details.

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FORMS: Forest Multiple Source height, wood volume, and… (Full Dataset)30.9 GB

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ReadmeVia DOI record

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Files are hosted on the source repository. Click download to access the full dataset.

Schwartz M. (2023). FORMS: Forest Multiple Source height, wood volume, and biomass maps in France at 10 to 30 m resolution based on Sentinel-1, Sentinel-2, and GEDI data with a deep learning approach.. https://doi.org/10.5281/zenodo.7840108

FORMS: Forest Multiple Source height, wood volume, and biomass maps in France at 10 to 30 m resolution based on Sentinel-1, Sentinel-2, and GEDI data with a deep learning approach.

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